Literature DB >> 722808

Evaluation of compositional nonrandomness in proteins.

R Holmquist.   

Abstract

Cornish-Bowden and Marson have recently suggested that the finite sampling component of Q, a measure of nonrandomness in the amino acid composition of proteins, may have been underestimated because it was calculated on the basis of the genetic code table frequencies rather than on the basis of the average natural abundance with which the twenty amino acids actually occur in proteins. This underestimate would lead to an overestimate of Qc a measure of selective effects above and beyond those imposed by the average natural abundance of the amino acids. In this paper the finite sampling component of Q is quantitatively estimated on the basis of these natural abundances and found to reduce Qc from its previous average value of 24.3 to the lower value of 9.7, with the standard deviation of the population of Qc values being 12.5. Individual Qc values are given for 81 protein families of mean composition per 61 codons of Ala5.3Arg2.4Asn3.0Asp3.6Cys1.5Gln2.6Glu3.5Gly4.7His1.3Ile3.4Leu4.5Lys4.2Met1.0Phe2.3Pro2.3Ser4.2Thr3.6Trp0.8Tyr2.6Val4.2. The mean Qc value of 9.7 is notably small, and indicates that quantitatively minimal adjustments away from the average protein composition are necessary to maintain many different biological functions. This small value, however, is shown to differ significantly from the value of zero expected were the natural abundances of the amino acids the only selective constraint. These small deviations from the natural abundances are thus effectively selected for in the Darwinian sense.

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Year:  1978        PMID: 722808     DOI: 10.1007/bf01733842

Source DB:  PubMed          Journal:  J Mol Evol        ISSN: 0022-2844            Impact factor:   2.395


  12 in total

Review 1.  Darwinian evolution in the genealogy of haemoglobin.

Authors:  M Goodman; G W Moore; G Matsuda
Journal:  Nature       Date:  1975-02-20       Impact factor: 49.962

2.  Tables of critical values for examining compositional non-randomness in proteins and nucleic acids.

Authors:  M Laird; R Holmquist
Journal:  J Mol Evol       Date:  1975-03-24       Impact factor: 2.395

3.  Detecting evolutionary trends from molecular data. 1. Some measures of compositional nonrandomness.

Authors:  H Vogel
Journal:  J Mol Evol       Date:  1975-12-29       Impact factor: 2.395

4.  Compositional nonrandomness: a quantitatively conserved evolutionary invariant.

Authors:  R Halmquist; H Moise
Journal:  J Mol Evol       Date:  1975-10-03       Impact factor: 2.395

5.  Stochastic versus augmented maximum parsimony method for estimating superimposed mutations in the divergent evolution of protein sequences. Methods tested on cytochrome c amino acid sequences.

Authors:  G W Moore; M Goodman; C Callahan; R Holmquist; H Moise
Journal:  J Mol Biol       Date:  1976-07-25       Impact factor: 5.469

6.  The amino acid sequence of a DNA binding protein, the gene 5 product of fd filamentous bacteriophage.

Authors:  Y Nakashima; A K Dunker; D A Marvin; W Konigsberg
Journal:  FEBS Lett       Date:  1974-04-01       Impact factor: 4.124

7.  Conservation of Shannon's redundancy for proteins.

Authors:  L L Gatlin
Journal:  J Mol Evol       Date:  1974       Impact factor: 2.395

8.  An improved method for determining codon variability in a gene and its application to the rate of fixation of mutations in evolution.

Authors:  W M Fitch; E Markowitz
Journal:  Biochem Genet       Date:  1970-10       Impact factor: 1.890

9.  Evaluation of the non-randomness of protein compositions.

Authors:  A Cornish-Bowden; A Marson
Journal:  J Mol Evol       Date:  1977-12-29       Impact factor: 2.395

10.  Amino acid composition of proteins: Selection against the genetic code.

Authors:  T H Jukes; R Holmquist; H Moise
Journal:  Science       Date:  1975-07-04       Impact factor: 47.728

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  3 in total

1.  Assimilatory sulfur metabolism in marine microorganisms: considerations for the application of sulfate incorporation into protein as a measurement of natural population protein synthesis.

Authors:  R L Cuhel; C D Taylor; H W Jannasch
Journal:  Appl Environ Microbiol       Date:  1982-01       Impact factor: 4.792

2.  The estimation of genetic divergence.

Authors:  R Holmquist; T Conroy
Journal:  J Mol Evol       Date:  1981       Impact factor: 2.395

3.  Theoretical foundations for quantitative paleogenetics. Part III: The molecular divergence of nucleic acids and proteins for the case of genetic events of unequal probability.

Authors:  R Holmquist; D Pearl
Journal:  J Mol Evol       Date:  1980-12       Impact factor: 2.395

  3 in total

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